Conversational AI with Rasa: Build,test,and deploy AI-powered,enterprise-grade virtual assistants and chatbots
8 Oct. 2021
Author: Xiaoquan Kong ,Guan Wang ,Alan Nichol (Foreword)
Publisher finelybook 出版社: Packt Publishing (8 Oct. 2021)
Language 语言: English
Print Length 页数: 264 pages
ISBN-10: 1801077053
ISBN-13: 9781801077057
Book Description
Create next-level AI assistants and transform how customers communicate with businesses with the power of natural language understanding and dialogue management using Rasa
Key Features
Understand the architecture and put the underlying principles of the Rasa framework to practice
Learn how to quickly build different types of chatbots such as task-oriented,FAQ-like,and knowledge graph-based chatbots
Explore best practices for working with Rasa and its debugging and optimizing aspects
The Rasa framework enables developers to create industrial-strength chatbots using state-of-the-art natural language processing (NLP) and machine learning technologies quickly,all in open source.
Conversational AI with Rasa starts Author: showing you how the two main components at the heart of Rasa work – Rasa NLU (natural language understanding) and Rasa Core. You’ll then learn how to build,configure,train,and serve different types of chatbots from scratch Author: using the Rasa ecosystem. As you advance,you’ll use form-based dialogue management,work with the response selector for chitchat and FAQ-like dialogs,make use of knowledge base actions to answer questions for dynamic queries,and much more. Furthermore,you’ll understand how to customize the Rasa framework,use conversation-driven development patterns and tools to develop chatbots,explore what your bot can do,and easily fix any mistakes it makes Author: using interactive learning. Finally,you’ll get to grips with deploying the Rasa system to a production environment with high performance and high scalability and cover best practices for building an efficient and robust chat system.
Author: the end of this book,you’ll be able to build and deploy your own chatbots using Rasa,addressing the common pain points encountered in the chatbot life cycle.
What you will learn
Use the response selector to handle chitchat and FAQs
Create custom actions using the Rasa SDK
Train Rasa to handle complex named entity recognition
Become skilled at building custom components in the Rasa framework
Validate and test dialogs end to end in Rasa
Develop and refine a chatbot system Author: using conversation-driven deployment processing
Use TensorBoard for tuning to find the best configuration options
Debug and optimize dialogue systems based on Rasa
